Optimization of urban settlement monitoring scheme based on hierarchical analysis

1. Introduction

With the continuous development of social economy, the footsteps of urbanization have gradually accelerated, and the number of urban populations is increasing. People have increased sharply to urban material resources, the most typical is over-exploitation of urban groundwater. It has caused the surface of the surface to segmentation, which seriously affects the sustainable development of the city. It can be seen that the sedimentary monitoring of urban surfaces is significant. [1] [2].

Currently, urban terrestrial settlement observation and application have a wide range of methods with traditional level measurement and GPS static monitoring. The advantages and disadvantages of the above two methods are also obvious [3] [4] [5]. Traditional level measurements are used for settlement observations with high measurement accuracy, easy to observe equipment, and simple work data processing, but in large-scale urban terrestrial settlement monitoring, China and foreign works is large and cost-effective [6] [7] [8] . GPS monitoring has high degree of automation, all-weather monitoring, but the instrument is relatively expensive and the satellite signal is largely interfered with external factors [9] [10] [11] [12]. An excellent settlement monitoring program not only has to be technically safe and reliable, but also needs to consider many elements such as economic and environment, which has both energy-quantitative elements, and some factors are difficult to quantify, so they need to practice according to expert practice. Personal experience gives reasonable choice. However, existing sinking observation programs in the existing expert qualitative analysis will choose to be large and subjective, and it is difficult to provide scientific reference for decision makers.

Accordingly, this paper proposes a preferred method of urban settlement monitoring scheme based on hierarchical analysis, and gives the influencing factors of monitoring work in different programs, and constructs urban ground settlement monitoring hierarchical model and corresponding knowledge according to expert experience. Judgment matrix, finally consistency with the results of the results of the results as the result of MATLAB, resulting in the weight of different urban terrestrial monitoring programs, and becomes a final program preferred decision basis.

2. Method

2.1. Urban terrestrial settlement monitoring hierarchy

Analytic Hierarchy Process, AHP first transforms the target layer into different hierarchies , Use mathematical matrix analysis and solve evaluation index [13] [14] [15][16]. According to the basic steps of large area settlement monitoring, the influencing factors of sedimentation monitoring are analyzed from the measurement accuracy, the plan budget, the selection network, the measurement error and the data processing, and the urban settlement monitoring based on hierarchical model is constructed. Scheme, as shown in

Fig. 1 .

Figure 1

. Urban Settlement Monitoring Scheme Structure Hierarchy Diagram

. Urban settlement monitoring scheme structure hierarchical diagram

Rule layer A mainly includes five factors. Among them, the measurement accuracy is a key influencing factor for the selection of settlement observation programs; the economic cost involved in the program budget is an important factor affecting the entire settlement monitoring project, mainly including measuring instruments, measurement personnel, and working days, so the plan is also required. Considering economic and savings; data processing affects the time of the entire monitoring scheme, the data processing difference between different programs is large, mainly considering baseline decisions and pulse difference calculations; selecting point network for GPS monitoring and level measurement The requirements are inconsistent, so it is also incorporated in consideration; the measurement error is similar to the measurement accuracy, and it is also an important influencing factor for program selection. Due to the relatively complexity of large area settling monitoring, the original rule layer branch is given a sub-standard layer B, and more accurate and objective analysis results can be obtained by adding more influencing factors. Among them, the program budget can be divided into instrument costs, the number of personnel, the number of days required to complete the entire settlement monitoring plan; the measurement error is generally homogenous, the three impact factors: the equipment itself, various external factors Error and human generated error.

2.2. Based on expert experience Construction Judgment Matrix

After determining the membership relationship between the target layer, the rule layer, and the decision layer, it is necessary to construct a judgment matrix for the target. During the judgment matrix structure, in order to make the influence, this paper is based on expert experience, this articleReference 1 to 9 Scales Methods The influencing factors were two-two comparisons [16] [17], as shown in

Table 1

. 1 indicates that the two factors have the same importance, and 3, 5, 7, 9 indicate that the two factors are slightly, obvious, strong, extremely important than the latter, respectively, and the remaining numbers are expressed as the intermediate value.

Table 1

. Meaning of Scale 1 ~ 9

Table 1 . 1 to 9 Scales Scale Meaning

The determination matrix A is:


11 12 22 ⋯ N ⋯ A ⋮ ⋮ A N A N ⋱ ⋮ N 2.3. Level Single Sorting and Consistency Inspection Weight W Representation The degree of size in the hierarchical order, separately: W , ⋯ , W , the specific solution process is as follows: First, the influence factor in the determination matrix A is normalized by column. As shown in formula (1): A i J i J σ N

A (1) A i J Normalized vector,


I J shows the elements in the determination matrix. Second, it will be normalized J i , as shown in formula (2): W i σ J = 1 i J Then, the newly obtained

W Vector normalized treatment can be obtained W i , as shown in formula (3): W i = W [12 σ J = N W i

W The characteristic vector of the finding is based on this formula (4) to calculate the maximum feature root λ MAX . λ MAX = = 1 N A W

N W i wherein A represents a determination matrix, n represents a dimension of the matrix, on this, based on this The formula (5) performs a consistency test indicator CI calculation.

C = λ – N – [ 1 Simultaneous consistency index Ri specific values ​​such as Table 2 Is shown. Table 2 . Ri Values ​​ Table 2 . Ri value C R = R i

(6) As shown in Equation (6), Cr represents a consistency ratio. When it is worth 0.1 hours, it is generally considered to be reasonable. 2.4. Total Sorting and Consistency Test The overall sorting of the hierarchy is used to determine the process of certain layers of elements relative to the overall objective importance. Specifically, equation (7) can be used. P i J


1 M J i (7) wherein indicates the weight value of the overall sorting of the hierarchy, specifically, as shown in the formula (8). A 1 B + A 2 B + ⋯ +



B : : 1 B + 2 B 22





1 B + A 2 B N + ⋯ + A M N M

The consistency ratio CR of the total sorting of the hierarchy (9) is employed. C r


1 C I + 2 C + ⋯ + a C i M A 1 R + A 2 2 + ⋯ + R M When the CR value is 0.1 hours, the total sorting of the hierarchy is reasonable, otherwise it is unreasonable. 3. Case analysis In this paper, the method optimized by the surface settlement of a city, and the analysis of the various layers of the surface settlement monitoring programs in the city were analyzed. Judging matrix. As shown in Fig. 2 . Figure 2 . The Monitoring Scheme Selects The Judgment Matrix of Each Level . Monitoring scheme is preferred to determine the matrix in Fig. 3 , the calculation is calculated using MATLAB. The maximum feature value and feature vector result of each matrix. Fighe 3 . Matlab Calculation Results Figure 3 . MATLAB calculation results For the judgment matrix AA, the maximum feature value λ MAX = 5.098 , normalized feature vector is W = 0.173 , 0.05 , 0.273 , the consistency index is C = 0.0245 , consistency ratio C R indicates that the judgment matrix is ​​reasonable and the result is inspected by consistency. . Similarly, the consistency ratio of other matrices can be obtained. Then you can find P 1 For the weight of the target layer Z layer is 0.57, P 2 The weight of the target layer Z layer is 0.43, it can be seen that the plan is a P 1 The ground settlement monitoring of the city is superior to the prime minus measurement using GPS, so that the solution is selected. 4. Conclusion This paper uses a hierarchical analysis method for optimization of urban settlement monitoring, and has carried out case analysis as an example of ground sinking monitoring. The results show that GPS is used in the city. Settlement monitoring is more scientifically reasonable, the main reason is that GPS is used for urban ground settlement monitoring not only expands the monitoring area, and the monitoring cost can also improve monitoring flexibility. It can also be seen that the use of hierarchical analysis can reduce the difficulty of the program selection and the impact of human subjective factors, and improve the objectivity and scientificity of final decision-making. Reference [1] Wang Jianwen. Application of precision level measurement technology in key settling area monitoring [D]: [Master’s thesis]. Xi’an: Xi’an University of Science and Technology, 2020. Langhui. Analysis and Application of Waiter Level in Foundation Pit Settlement Monitoring [J]. Fujian Building Materials, 2020 (8): 20- 21 + 27. Xie Xuhui, Xu Xiwen. Senior Building Descertrome Measurement Based on High-precision Level Measurement [J] .Jiangxi Building Materials, 2018 (13): 41-42 Wang Thunder. On the application of precision level measurement in terrestrial settlement monitoring [J]. North China Land and Resources, 2013 (2): 113-116. Qin Hongkui, Wang Pingde. GPS is used in Tianjin ground settlement monitoring in the surveillance monitoring of Tianjin [J]. Surveying and Mapping Information and Engineering, 2012, 37 (2): 20-21. [6] Xu Ziping.Application of Digital Glass In Settlement Observations [J] .Shaisse Building, 2019, 45 (22): 146-148.

[ 7]

Lin Lixiang. Application of Triangle Elevation in Pavement in Pavement Settles [J]. 土 土 基, 2019, 33 (2): 215-219. Wang Mingyue, Pan Ying, Huangyang.Analysis of the segmentation observation method of large commercial building [J]. Modern Semism, 2015, 38 (2) : 23-25. [9] CHEN, J., YUE, D., Liu, Z., et al. (2019) Experimental ResEarch On Daily DEFORMATION MONITORING OF BRIDGE USING BDS / GPS. Survey Review, 51, 472-482. TU, R., Liu, J., Lu, C., et al. (2017) Cooperating the BDS, GPS, GLONASS AND STRONG -Motion Observations for Real-Time DEFORMATION MONITORING. Geophysical Journals, 209, 1408-1417. / gji / ggX099 Hu Jut, Liu Dajie. GPS measurement based on GPS base station [J] Modern Surveying 2003 (1): 10-13. [12] Yi Changrong, Wang Wei, Xu Dong. GPS continuous station monitoring Tianjin ground settlement preliminary results [J]. Modern Surveying, 2009, 32 (1): 31-33 Zhu Qing, Chen Kaihao, Xie Wei, et al. Fuzzy hierarchy analysis and three-dimensional GIS integrated boosting station selection Some Method [J]. Journal of Southwest Jiaotong University, 2019, 54 (5): 980-988. Xu Yongxi. Evaluation of rural tourism resources in Nanling County based on level analysis [J]. Anhui Agricultural News, 2020, 26 (24): 159 -162. Cheng Yu, Lu Feng, Fan Rui, Zhu Min. Research on Side Model of Growth Geography Based on AHP Construction [J]. Modern Surveying, 2018, 41 (6): 29-32. Jia Tao. Risk assessment of mudslide disaster in Songpan Section, Chenglan Railway [D]: [Master’s thesis]. Chengdu: Chengdu University of Technology, 2015. [17] Liu Hengcheng, Gu Xiuzhi.Study on Dangerous Evaluation of Debris Flow Based on Extension Analysis [J]. Journal of Geological Hazard and Prevention, 2010, 21 (3): 61 -66.

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